There is little doubt that eye-tracking provides valuable insight into the current mental state and problem solving strategy of a human subject. The human retina is anisotropic, and has a high-resolution fovea surrounded by a much lower resolution peripheral retina. In order for this architecture to work properly, the eyes must move rapidly about the scene. The net effect of this movement, is the illusion that the human vision system (HVS) has both a large field-of-view and a high acuity across the entire visual field. What is actually happening, however, is that the rapid movements of the eye are sequentially capturing the information needed to solve a particular problem. It is the fact that eyes acquire information in small amounts and in a sequential manner that makes eye-tracking so important to understanding the state of the human subject. It is the only tool that allows a researcher to explore the portions of the cognitive process that cannot be articulated.
The research literature is filled with eye-tracking studies that validate that statement, and illustrate that eye-tracking can be used to measure learning. For example, eye-tracking was used to show strategic game playing differences between novice and expert players of the game Tetris. As reported, expert players do not play the game faster than novice players. Quite the contrary. Experts stretch out the placement of the current piece for as long as possible so that they can concentrate on where to place the next piece. This is actually a clever strategy that maximizes decision time. Although the expert player could not articulate this strategy, it was clearly evident in the eye movement histories. The novice player simply focused on placing the current piece, and in fact, played the game at a much faster rate than the expert. This simple example illustrates the power that eye-tracking has on uncovering non-intuitive problem solving strategies and the potential that eye-tracking has for developing measures of performance and training methods.
Although current methods of eye-tracking have demonstrated tremendous potential for the use of this data, they have fallen short in their overall ability to facilitate widespread use of this technology for training. Many of these methods capture and process a video stream of the working eye, and require extensive image processing methods to obtain eye position information. Unfortunately, these contemporary eye-trackers fall short of perfection, and as a result, they have received much criticism: they are too expensive, they are too difficult or cumbersome to wear, they are too hard to use, a chin rest or bite bar may be required to restrict head movement, they do not work for individuals that wear glasses or contact lenses, they require frequent calibrations and recalibrations, and the data they collect can be corrupted by blinks or glances.
In short, current eye-tracking methods are far from perfect, and none of the current devices completely satisfy all the requirements identified for an ideal eye-tracker. Alternative approaches to eye-tracking based on video oculography (VOG), infrared oculography (IROG), and electro-oculography (EOG) methods have also been developed.
The VOG approach relies on determining the relative position of the subject's cornea and a glint of infrared light reflected off the pupil. An infrared emitter is used to produce the glint and a video camera is used to capture a sequence of images that contain the glint and subject's eye. Image processing techniques are used to determine the position of the cornea and the glint. The position of the glint relative to the cornea changes as the eye moves. Thus, a VOG-based eye-tracker calculates eye position based on the relative position of the cornea and the reflected pupil glint. In general, this method of eye-tracking requires an infrared emitter and a video camera mounted to maintain a fixed relationship to the subject's eye that often results in cumbersome and expensive eye-tracking devices. This method has good spatial and temporal resolution, but head movements and eye blinks can effect image quality and tracking performance.
The IROG approach relies on measuring the intensity of infrared light reflected back from the subject's eye. Infrared emitters and infrared detectors are located in fixed positions around the eye. The amount of light reflected back to a fixed detector varies with eye position. Thus, an IROG-based eye-tracker calculates eye position based on the amount of reflected infrared light. In general, this method of eye-tracking requires goggles with mounted infrared emitters and detectors, and such devices are often both intrusive and expensive. This method has good spatial resolution and high temporal resolution, but is better for measuring horizontal than vertical eye movements and has difficulty with eye blinks which alter the amount of reflected light.
The EOG approach relies on the fact that the eye has a standing electrical potential across it with the front of the eye positive and the back of the eye negative. This potential varies from one to several millivolts, depending on the individual and illumination levels. EOG is measured by placing electrodes above and below the eye and on the outside of each eye. Changes in the EOG signals are directly related to changes in eye position. Thus, an EOG-based eye-tracker calculates eye position based on these signals. In general, this method of eye-tracking requires extensive calibration and lacks the precision needed for many eye-tracking applications. Foveated or gaze-contingent variable-resolution displays have been well developed in previous works. Foveated display techniques select the foveated region by actively tracking the subject's eyes and presenting an area of high spatial resolution at the point of gaze. Widespread application of such displays has been slowed by several difficulties. The technique requires fast and continuous tracking of the gaze point, and previous eyetrackers have been too expensive for widespread application, too imprecise, or too invasive for routine use. At present, the widespread use of gaze-contingent applications depends primarily on the development of low-cost eye-tracking systems.